Autonomy first route optimization for autonomous vehicles

ABSTRACT

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application claims the benefits of and priority, under 35U.S.C. § 119(e), to U.S. Provisional Application Ser. No. 62/424,976,filed on Nov. 21, 2016, entitled “Next Generation Vehicle,” the entiredisclosure of which is hereby incorporated by reference, in itsentirety, for all that it teaches and for all purposes.

FIELD

The present disclosure is generally directed to vehicle systems, inparticular, toward autonomous or self-driving vehicles.

BACKGROUND

In recent years, transportation methods have changed substantially. Thedesire to drive has waned and the number of accidents attributed todriver distraction has increased. Generally, people are turning todriverless features in vehicles more often. While some vehicles are ableto drive autonomously, it is still difficult to determine whenautonomous driving can be used or where it is best used.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a vehicle in accordance with embodiments of the presentdisclosure;

FIG. 2 shows a plan view of the vehicle in accordance with at least someembodiments of the present disclosure;

FIG. 3A is a block diagram of an embodiment of a communicationenvironment of the vehicle in accordance with embodiments of the presentdisclosure;

FIG. 3B is a block diagram of an embodiment of interior sensors withinthe vehicle in accordance with embodiments of the present disclosure;

FIG. 3C is a block diagram of an embodiment of a navigation system ofthe vehicle in accordance with embodiments of the present disclosure;

FIG. 4 shows an embodiment of the instrument panel of the vehicleaccording to one embodiment of the present disclosure;

FIG. 5 is a block diagram of an embodiment of a communications subsystemof the vehicle;

FIG. 6 is a block diagram of a computing environment associated with theembodiments presented herein;

FIG. 7 is a block diagram of a computing device associated with one ormore components described herein;

FIG. 8 is a block diagram of a computing system associated with one ormore components described herein;

FIG. 9A is a data diagram of route characteristics according toembodiments of the present disclosure;

FIG. 9B is a data diagram of route characteristics according toembodiments of the present disclosure;

FIG. 9C is a data diagram of user/vehicle characteristics according toembodiments of the present disclosure; and

FIG. 10 is a flow diagram of an embodiment of a method for determining abest route for autonomous driving according to embodiments of thepresent disclosure.

DETAILED DESCRIPTION

Embodiments of the present disclosure will be described in connectionwith a vehicle, and in some embodiments, an electric vehicle,rechargeable electric vehicle, and/or hybrid-electric vehicle andassociated systems. Some embodiments relate to an autonomous vehicle orself-driving vehicle.

Systems and methods herein can determine an optimal route for anautonomous electric vehicle. The system may score viable routes betweenthe start and end locations of a trip using a numeric or other scalethat denotes how viable the route is for autonomy. The score is adjustedusing a variety of factors where a learning process leverages bothoffline and online data. Offline learning may be based on factors suchas: the average number of lanes in each route segment along every viableroute, the average number of traffic lights, the number of school zones,stop signs, and yield signs, the number of lane merges, the averagespeed limits, historical traffic or road occupant density for differentcategories of road occupants such as motorcycles, cars, trucks,cyclists, and pedestrians, etc. Any traffic or occupant density modelcan be constantly or consistently updated as more data is gathered andmore occupants are observed.

An online process can augment the learned score with additional realtime data including but not limited to: the current state of electriccharge, a battery discharge profile for each route, the occupant'simplicit preference for each route computed as a function of severalfactors, for example, the average number of traffic lights along theroute, the average number of lanes, the average speed limit, the sceneryappeal, etc., a current state of traffic and road condition(s)determined from crowd-sourced information originating from a network ofvehicles, occupant's current activity in the vehicle (e.g., meeting vs.just commuting), etc. Other information can also effect the routeselection including, but not limited to: location of charging optionsavailable to the user, a user's driving habits, a user's calendarinformation, etc.

Advantages of the algorithm is in improving end-user experience and inimproving the efficiency of an autonomous vehicle. In some situations,the vehicle can match a known calendar event, and can choose a longerroute to have phone conversation while traveling. In other situations,the shortest route based on time or distance using the autonomousdriving capability (which may be different than the shortest route formanual driving) can be chosen. In other words, the route is based on thedriving context rather than just on geographical information (i.e., mapdata). While there may be a computational cost incurred in makingdecisions with the data available, the decisions will save time and/orimprove the user's experience.

Embodiments of the present disclosure will be described in connectionwith a vehicle, and in some embodiments, an electric vehicle,rechargeable electric vehicle, and/or hybrid-electric vehicle andassociated systems.

FIG. 1 shows a perspective view of a vehicle 100 in accordance withembodiments of the present disclosure. The electric vehicle 100comprises a vehicle front 110, vehicle aft or rear 120, vehicle roof130, at least one vehicle side 160, a vehicle undercarriage 140, and avehicle interior 150. In any event, the vehicle 100 may include a frame104 and one or more body panels 108 mounted or affixed thereto. Thevehicle 100 may include one or more interior components (e.g.,components inside an interior space 150, or user space, of a vehicle100, etc.), exterior components (e.g., components outside of theinterior space 150, or user space, of a vehicle 100, etc.), drivesystems, controls systems, structural components, etc.

Although shown in the form of a car, it should be appreciated that thevehicle 100 described herein may include any conveyance or model of aconveyance, where the conveyance was designed for the purpose of movingone or more tangible objects, such as people, animals, cargo, and thelike. The term “vehicle” does not require that a conveyance moves or iscapable of movement. Typical vehicles may include but are in no waylimited to cars, trucks, motorcycles, busses, automobiles, trains,railed conveyances, boats, ships, marine conveyances, submarineconveyances, airplanes, space craft, flying machines, human-poweredconveyances, and the like.

In some embodiments, the vehicle 100 may include a number of sensors,devices, and/or systems that are capable of assisting in drivingoperations. Examples of the various sensors and systems may include, butare in no way limited to, one or more of cameras (e.g., independent,stereo, combined image, etc.), infrared (IR) sensors, radio frequency(RF) sensors, ultrasonic sensors (e.g., transducers, transceivers,etc.), RADAR sensors (e.g., object-detection sensors and/or systems),LIDAR systems, odometry sensors and/or devices (e.g., encoders, etc.),orientation sensors (e.g., accelerometers, gyroscopes, magnetometer,etc.), navigation sensors and systems (e.g., GPS, etc.), and otherranging, imaging, and/or object-detecting sensors. The sensors may bedisposed in an interior space 150 of the vehicle 100 and/or on anoutside of the vehicle 100. In some embodiments, the sensors and systemsmay be disposed in one or more portions of a vehicle 100 (e.g., theframe 104, a body panel, a compartment, etc.).

The vehicle sensors and systems may be selected and/or configured tosuit a level of operation associated with the vehicle 100. Among otherthings, the number of sensors used in a system may be altered toincrease or decrease information available to a vehicle control system(e.g., affecting control capabilities of the vehicle 100). Additionallyor alternatively, the sensors and systems may be part of one or moreadvanced driver assistance systems (ADAS) associated with a vehicle 100.In any event, the sensors and systems may be used to provide drivingassistance at any level of operation (e.g., from fully-manual tofully-autonomous operations, etc.) as described herein.

The various levels of vehicle control and/or operation can be describedas corresponding to a level of autonomy associated with a vehicle 100for vehicle driving operations. For instance, at Level 0, orfully-manual driving operations, a driver (e.g., a human driver) may beresponsible for all the driving control operations (e.g., steering,accelerating, braking, etc.) associated with the vehicle. Level 0 may bereferred to as a “No Automation” level. At Level 1, the vehicle may beresponsible for a limited number of the driving operations associatedwith the vehicle, while the driver is still responsible for most drivingcontrol operations. An example of a Level 1 vehicle may include avehicle in which the throttle control and/or braking operations may becontrolled by the vehicle (e.g., cruise control operations, etc.). Level1 may be referred to as a “Driver Assistance” level. At Level 2, thevehicle may collect information (e.g., via one or more drivingassistance systems, sensors, etc.) about an environment of the vehicle(e.g., surrounding area, roadway, traffic, ambient conditions, etc.) anduse the collected information to control driving operations (e.g.,steering, accelerating, braking, etc.) associated with the vehicle. In aLevel 2 autonomous vehicle, the driver may be required to perform otheraspects of driving operations not controlled by the vehicle. Level 2 maybe referred to as a “Partial Automation” level. It should be appreciatedthat Levels 0-2 all involve the driver monitoring the driving operationsof the vehicle.

At Level 3, the driver may be separated from controlling all the drivingoperations of the vehicle except when the vehicle makes a request forthe operator to act or intervene in controlling one or more drivingoperations. In other words, the driver may be separated from controllingthe vehicle unless the driver is required to take over for the vehicle.Level 3 may be referred to as a “Conditional Automation” level. At Level4, the driver may be separated from controlling all the drivingoperations of the vehicle and the vehicle may control driving operationseven when a user fails to respond to a request to intervene. Level 4 maybe referred to as a “High Automation” level. At Level 5, the vehicle cancontrol all the driving operations associated with the vehicle in alldriving modes. The vehicle in Level 5 may continually monitor traffic,vehicular, roadway, and/or environmental conditions while driving thevehicle. In Level 5, there is no human driver interaction required inany driving mode. Accordingly, Level 5 may be referred to as a “FullAutomation” level. It should be appreciated that in Levels 3-5 thevehicle, and/or one or more automated driving systems associated withthe vehicle, monitors the driving operations of the vehicle and thedriving environment.

As shown in FIG. 1, the vehicle 100 may, for example, include at leastone of a ranging and imaging system 112 (e.g., LIDAR, etc.), an imagingsensor 116A, 116F (e.g., camera, IR, etc.), a radio object-detection andranging system sensors 116B (e.g., RADAR, RF, etc.), ultrasonic sensors116C, and/or other object-detection sensors 116D, 116E. In someembodiments, the LIDAR system 112 and/or sensors may be mounted on aroof 130 of the vehicle 100. In one embodiment, the RADAR sensors 116Bmay be disposed at least at a front 110, aft 120, or side 160 of thevehicle 100. Among other things, the RADAR sensors may be used tomonitor and/or detect a position of other vehicles, pedestrians, and/orother objects near, or proximal to, the vehicle 100. While shownassociated with one or more areas of a vehicle 100, it should beappreciated that any of the sensors and systems 116A-K, 112 illustratedin FIGS. 1 and 2 may be disposed in, on, and/or about the vehicle 100 inany position, area, and/or zone of the vehicle 100.

Referring now to FIG. 2, a plan view of a vehicle 100 will be describedin accordance with embodiments of the present disclosure. In particular,FIG. 2 shows a vehicle sensing environment 200 at least partiallydefined by the sensors and systems 116A-K, 112 disposed in, on, and/orabout the vehicle 100. Each sensor 116A-K may include an operationaldetection range R and operational detection angle. The operationaldetection range R may define the effective detection limit, or distance,of the sensor 116A-K. In some cases, this effective detection limit maybe defined as a distance from a portion of the sensor 116A-K (e.g., alens, sensing surface, etc.) to a point in space offset from the sensor116A-K. The effective detection limit may define a distance, beyondwhich, the sensing capabilities of the sensor 116A-K deteriorate, failto work, or are unreliable. In some embodiments, the effective detectionlimit may define a distance, within which, the sensing capabilities ofthe sensors 116A-K are able to provide accurate and/or reliabledetection information. The operational detection angle may define atleast one angle of a span, or between horizontal and/or vertical limits,of a sensor 116A-K. As can be appreciated, the operational detectionlimit and the operational detection angle of a sensor 116A-K togethermay define the effective detection zone 216A-D (e.g., the effectivedetection area, and/or volume, etc.) of a sensor 116A-K.

In some embodiments, the vehicle 100 may include a ranging and imagingsystem 112 such as LIDAR, or the like. The ranging and imaging system112 may be configured to detect visual information in an environmentsurrounding the vehicle 100. The visual information detected in theenvironment surrounding the ranging and imaging system 112 may beprocessed (e.g., via one or more sensor and/or system processors, etc.)to generate a complete 360-degree view of an environment 200 around thevehicle. The ranging and imaging system 112 may be configured togenerate changing 360-degree views of the environment 200 in real-time,for instance, as the vehicle 100 drives. In some cases, the ranging andimaging system 112 may have an effective detection limit 204 that issome distance from the center of the vehicle 100 outward over 360degrees. The effective detection limit 204 of the ranging and imagingsystem 112 defines a view zone 208 (e.g., an area and/or volume, etc.)surrounding the vehicle 100. Any object falling outside of the view zone208 is in the undetected zone 212 and would not be detected by theranging and imaging system 112 of the vehicle 100.

Sensor data and information may be collected by one or more sensors orsystems 116A-K, 112 of the vehicle 100 monitoring the vehicle sensingenvironment 200. This information may be processed (e.g., via aprocessor, computer-vision system, etc.) to determine targets (e.g.,objects, signs, people, markings, roadways, conditions, etc.) inside oneor more detection zones 208, 216A-D associated with the vehicle sensingenvironment 200. In some cases, information from multiple sensors 116A-Kmay be processed to form composite sensor detection information. Forexample, a first sensor 116A and a second sensor 116F may correspond toa first camera 116A and a second camera 116F aimed in a forwardtraveling direction of the vehicle 100. In this example, imagescollected by the cameras 116A, 116F may be combined to form stereo imageinformation. This composite information may increase the capabilities ofa single sensor in the one or more sensors 116A-K by, for example,adding the ability to determine depth associated with targets in the oneor more detection zones 208, 216A-D. Similar image data may be collectedby rear view cameras (e.g., sensors 116G, 116H) aimed in a rearwardtraveling direction vehicle 100.

In some embodiments, multiple sensors 116A-K may be effectively joinedto increase a sensing zone and provide increased sensing coverage. Forinstance, multiple RADAR sensors 116B disposed on the front 110 of thevehicle may be joined to provide a zone 216B of coverage that spansacross an entirety of the front 110 of the vehicle. In some cases, themultiple RADAR sensors 116B may cover a detection zone 216B thatincludes one or more other sensor detection zones 216A. Theseoverlapping detection zones may provide redundant sensing, enhancedsensing, and/or provide greater detail in sensing within a particularportion (e.g., zone 216A) of a larger zone (e.g., zone 216B).Additionally or alternatively, the sensors 116A-K of the vehicle 100 maybe arranged to create a complete coverage, via one or more sensing zones208, 216A-D around the vehicle 100. In some areas, the sensing zones216C of two or more sensors 116D, 116E may intersect at an overlap zone220. In some areas, the angle and/or detection limit of two or moresensing zones 216C, 216D (e.g., of two or more sensors 116E, 116J, 116K)may meet at a virtual intersection point 224.

The vehicle 100 may include a number of sensors 116E, 116G, 116H, 116J,116K disposed proximal to the rear 120 of the vehicle 100. These sensorscan include, but are in no way limited to, an imaging sensor, camera,IR, a radio object-detection and ranging sensors, RADAR, RF, ultrasonicsensors, and/or other object-detection sensors. Among other things,these sensors 116E, 116G, 116H, 116J, 116K may detect targets near orapproaching the rear of the vehicle 100. For example, another vehicleapproaching the rear 120 of the vehicle 100 may be detected by one ormore of the ranging and imaging system (e.g., LIDAR) 112, rear-viewcameras 116G, 116H, and/or rear facing RADAR sensors 116J, 116K. Asdescribed above, the images from the rear-view cameras 116G, 116H may beprocessed to generate a stereo view (e.g., providing depth associatedwith an object or environment, etc.) for targets visible to both cameras116G, 116H. As another example, the vehicle 100 may be driving and oneor more of the ranging and imaging system 112, front-facing cameras116A, 116F, front-facing RADAR sensors 116B, and/or ultrasonic sensors116C may detect targets in front of the vehicle 100. This approach mayprovide critical sensor information to a vehicle control system in atleast one of the autonomous driving levels described above. Forinstance, when the vehicle 100 is driving autonomously (e.g., Level 3,Level 4, or Level 5) and detects other vehicles stopped in a travelpath, the sensor detection information may be sent to the vehiclecontrol system of the vehicle 100 to control a driving operation (e.g.,braking, decelerating, etc.) associated with the vehicle 100 (in thisexample, slowing the vehicle 100 as to avoid colliding with the stoppedother vehicles). As yet another example, the vehicle 100 may beoperating and one or more of the ranging and imaging system 112, and/orthe side-facing sensors 116D, 116E (e.g., RADAR, ultrasonic, camera,combinations thereof, and/or other type of sensor), may detect targetsat a side of the vehicle 100. It should be appreciated that the sensors116A-K may detect a target that is both at a side 160 and a front 110 ofthe vehicle 100 (e.g., disposed at a diagonal angle to a centerline ofthe vehicle 100 running from the front 110 of the vehicle 100 to therear 120 of the vehicle). Additionally or alternatively, the sensors116A-K may detect a target that is both, or simultaneously, at a side160 and a rear 120 of the vehicle 100 (e.g., disposed at a diagonalangle to the centerline of the vehicle 100).

FIG. 3 is a is a block diagram of an embodiment of a communicationenvironment 300 of the vehicle 100 in accordance with embodiments of thepresent disclosure. The communication system 300 may include one or morevehicle driving vehicle sensors and systems 304, sensor processors 340,sensor data memory 344, vehicle control system 348, communicationssubsystem 350, control data 364, computing devices 368, display devices372, and other components 374 that may be associated with a vehicle 100.These associated components may be electrically and/or communicativelycoupled to one another via at least one bus 360. In some embodiments,the one or more associated components may send and/or receive signalsacross a communication network 352 to at least one of a navigationsource 356A, a control source 356B, or some other entity 356N.

In accordance with at least some embodiments of the present disclosure,the communication network 352 may comprise any type of knowncommunication medium or collection of communication media and may useany type of protocols, such as SIP, TCP/IP, SNA, IPX, AppleTalk, and thelike, to transport messages between endpoints. The communication network352 may include wired and/or wireless communication technologies. TheInternet is an example of the communication network 352 that constitutesan Internet Protocol (IP) network consisting of many computers,computing networks, and other communication devices located all over theworld, which are connected through many telephone systems and othermeans. Other examples of the communication network 104 include, withoutlimitation, a standard Plain Old Telephone System (POTS), an IntegratedServices Digital Network (ISDN), the Public Switched Telephone Network(PSTN), a Local Area Network (LAN), such as an Ethernet network, aToken-Ring network and/or the like, a Wide Area Network (WAN), a virtualnetwork, including without limitation a virtual private network (“VPN”);the Internet, an intranet, an extranet, a cellular network, an infra-rednetwork; a wireless network (e.g., a network operating under any of theIEEE 802.9 suite of protocols, the Bluetooth® protocol known in the art,and/or any other wireless protocol), and any other type ofpacket-switched or circuit-switched network known in the art and/or anycombination of these and/or other networks. In addition, it can beappreciated that the communication network 352 need not be limited toany one network type, and instead may be comprised of a number ofdifferent networks and/or network types. The communication network 352may comprise a number of different communication media such as coaxialcable, copper cable/wire, fiber-optic cable, antennas fortransmitting/receiving wireless messages, and combinations thereof.

The driving vehicle sensors and systems 304 may include at least onenavigation 308 (e.g., global positioning system (GPS), etc.),orientation 312, odometry 316, LIDAR 320, RADAR 324, ultrasonic 328,camera 332, infrared (IR) 336, and/or other sensor or system 338. Thesedriving vehicle sensors and systems 304 may be similar, if notidentical, to the sensors and systems 116A-K, 112 described inconjunction with FIGS. 1 and 2.

The navigation sensor 308 may include one or more sensors havingreceivers and antennas that are configured to utilize a satellite-basednavigation system including a network of navigation satellites capableof providing geolocation and time information to at least one componentof the vehicle 100. Examples of the navigation sensor 308 as describedherein may include, but are not limited to, at least one of Garmin® GLO™family of GPS and GLONASS combination sensors, Garmin® GPS 15x™ familyof sensors, Garmin® GPS 16x™ family of sensors with high-sensitivityreceiver and antenna, Garmin® GPS 18x OEM family of high-sensitivity GPSsensors, Dewetron DEWE-VGPS series of GPS sensors, GlobalSat 1-Hz seriesof GPS sensors, other industry-equivalent navigation sensors and/orsystems, and may perform navigational and/or geolocation functions usingany known or future-developed standard and/or architecture.

The orientation sensor 312 may include one or more sensors configured todetermine an orientation of the vehicle 100 relative to at least onereference point. In some embodiments, the orientation sensor 312 mayinclude at least one pressure transducer, stress/strain gauge,accelerometer, gyroscope, and/or geomagnetic sensor. Examples of thenavigation sensor 308 as described herein may include, but are notlimited to, at least one of Bosch Sensortec BMX 160 series low-powerabsolute orientation sensors, Bosch Sensortec BMX055 9-axis sensors,Bosch Sensortec BMI055 6-axis inertial sensors, Bosch Sensortec BMI1606-axis inertial sensors, Bosch Sensortec BMF055 9-axis inertial sensors(accelerometer, gyroscope, and magnetometer) with integrated Cortex M0+microcontroller, Bosch Sensortec BMP280 absolute barometric pressuresensors, Infineon TLV493D-A1B6 3D magnetic sensors, InfineonTLI493D-W1B6 3D magnetic sensors, Infineon TL family of 3D magneticsensors, Murata Electronics SCC2000 series combined gyro sensor andaccelerometer, Murata Electronics SCC1300 series combined gyro sensorand accelerometer, other industry-equivalent orientation sensors and/orsystems, and may perform orientation detection and/or determinationfunctions using any known or future-developed standard and/orarchitecture.

The odometry sensor and/or system 316 may include one or more componentsthat is configured to determine a change in position of the vehicle 100over time. In some embodiments, the odometry system 316 may utilize datafrom one or more other sensors and/or systems 304 in determining aposition (e.g., distance, location, etc.) of the vehicle 100 relative toa previously measured position for the vehicle 100. Additionally oralternatively, the odometry sensors 316 may include one or moreencoders, Hall speed sensors, and/or other measurement sensors/devicesconfigured to measure a wheel speed, rotation, and/or number ofrevolutions made over time. Examples of the odometry sensor/system 316as described herein may include, but are not limited to, at least one ofInfineon TLE4924/26/27/28C high-performance speed sensors, InfineonTL4941plusC(B) single chip differential Hall wheel-speed sensors,Infineon TL5041plusC Giant Mangnetoresistance (GMR) effect sensors,Infineon TL family of magnetic sensors, EPC Model 25SP Accu-CoderPro™incremental shaft encoders, EPC Model 30M compact incremental encoderswith advanced magnetic sensing and signal processing technology, EPCModel 925 absolute shaft encoders, EPC Model 958 absolute shaftencoders, EPC Model MA36S/MA63S/SA36S absolute shaft encoders, Dynapar™F18 commutating optical encoder, Dynapar™ HS35R family of phased arrayencoder sensors, other industry-equivalent odometry sensors and/orsystems, and may perform change in position detection and/ordetermination functions using any known or future-developed standardand/or architecture.

The LIDAR sensor/system 320 may include one or more componentsconfigured to measure distances to targets using laser illumination. Insome embodiments, the LIDAR sensor/system 320 may provide 3D imagingdata of an environment around the vehicle 100. The imaging data may beprocessed to generate a full 360-degree view of the environment aroundthe vehicle 100. The LIDAR sensor/system 320 may include a laser lightgenerator configured to generate a plurality of target illuminationlaser beams (e.g., laser light channels). In some embodiments, thisplurality of laser beams may be aimed at, or directed to, a rotatingreflective surface (e.g., a mirror) and guided outwardly from the LIDARsensor/system 320 into a measurement environment. The rotatingreflective surface may be configured to continually rotate 360 degreesabout an axis, such that the plurality of laser beams is directed in afull 360-degree range around the vehicle 100. A photodiode receiver ofthe LIDAR sensor/system 320 may detect when light from the plurality oflaser beams emitted into the measurement environment returns (e.g.,reflected echo) to the LIDAR sensor/system 320. The LIDAR sensor/system320 may calculate, based on a time associated with the emission of lightto the detected return of light, a distance from the vehicle 100 to theilluminated target. In some embodiments, the LIDAR sensor/system 320 maygenerate over 2.0 million points per second and have an effectiveoperational range of at least 100 meters. Examples of the LIDARsensor/system 320 as described herein may include, but are not limitedto, at least one of Velodyne® LiDAR™ HDL-64E 64-channel LIDAR sensors,Velodyne® LiDAR™ HDL-32E 32-channel LIDAR sensors, Velodyne® LiDAR™PUCK™ VLP-16 16-channel LIDAR sensors, Leica Geosystems Pegasus:Twomobile sensor platform, Garmin® LIDAR-Lite v3 measurement sensor,Quanergy M8 LiDAR sensors, Quanergy S3 solid state LiDAR sensor,LeddarTech® LeddarVU compact solid state fixed-beam LIDAR sensors, otherindustry-equivalent LIDAR sensors and/or systems, and may performilluminated target and/or obstacle detection in an environment aroundthe vehicle 100 using any known or future-developed standard and/orarchitecture.

The RADAR sensors 324 may include one or more radio components that areconfigured to detect objects/targets in an environment of the vehicle100. In some embodiments, the RADAR sensors 324 may determine adistance, position, and/or movement vector (e.g., angle, speed, etc.)associated with a target over time. The RADAR sensors 324 may include atransmitter configured to generate and emit electromagnetic waves (e.g.,radio, microwaves, etc.) and a receiver configured to detect returnedelectromagnetic waves. In some embodiments, the RADAR sensors 324 mayinclude at least one processor configured to interpret the returnedelectromagnetic waves and determine locational properties of targets.Examples of the RADAR sensors 324 as described herein may include, butare not limited to, at least one of Infineon RASIC™ RTN7735PLtransmitter and RRN7745PL/46PL receiver sensors, Autoliv ASP VehicleRADAR sensors, Delphi L2C0051TR 77 GHz ESR Electronically Scanning Radarsensors, Fujitsu Ten Ltd. Automotive Compact 77 GHz 3D Electronic ScanMillimeter Wave Radar sensors, other industry-equivalent RADAR sensorsand/or systems, and may perform radio target and/or obstacle detectionin an environment around the vehicle 100 using any known orfuture-developed standard and/or architecture.

The ultrasonic sensors 328 may include one or more components that areconfigured to detect objects/targets in an environment of the vehicle100. In some embodiments, the ultrasonic sensors 328 may determine adistance, position, and/or movement vector (e.g., angle, speed, etc.)associated with a target over time. The ultrasonic sensors 328 mayinclude an ultrasonic transmitter and receiver, or transceiver,configured to generate and emit ultrasound waves and interpret returnedechoes of those waves. In some embodiments, the ultrasonic sensors 328may include at least one processor configured to interpret the returnedultrasonic waves and determine locational properties of targets.Examples of the ultrasonic sensors 328 as described herein may include,but are not limited to, at least one of Texas Instruments TIDA-00151automotive ultrasonic sensor interface IC sensors, MaxBotix® MB8450ultrasonic proximity sensor, MaxBotix® ParkSonar™-EZ ultrasonicproximity sensors, Murata Electronics MA40H1S-R open-structureultrasonic sensors, Murata Electronics MA40S4R/S open-structureultrasonic sensors, Murata Electronics MA58MF14-7N waterproof ultrasonicsensors, other industry-equivalent ultrasonic sensors and/or systems,and may perform ultrasonic target and/or obstacle detection in anenvironment around the vehicle 100 using any known or future-developedstandard and/or architecture.

The camera sensors 332 may include one or more components configured todetect image information associated with an environment of the vehicle100. In some embodiments, the camera sensors 332 may include a lens,filter, image sensor, and/or a digital image processer. It is an aspectof the present disclosure that multiple camera sensors 332 may be usedtogether to generate stereo images providing depth measurements.Examples of the camera sensors 332 as described herein may include, butare not limited to, at least one of ON Semiconductor® MT9V024 GlobalShutter VGA GS CMOS image sensors, Teledyne DALSA Falcon2 camerasensors, CMOSIS CMV50000 high-speed CMOS image sensors, otherindustry-equivalent camera sensors and/or systems, and may performvisual target and/or obstacle detection in an environment around thevehicle 100 using any known or future-developed standard and/orarchitecture.

The infrared (IR) sensors 336 may include one or more componentsconfigured to detect image information associated with an environment ofthe vehicle 100. The IR sensors 336 may be configured to detect targetsin low-light, dark, or poorly-lit environments. The IR sensors 336 mayinclude an IR light emitting element (e.g., IR light emitting diode(LED), etc.) and an IR photodiode. In some embodiments, the IRphotodiode may be configured to detect returned IR light at or about thesame wavelength to that emitted by the IR light emitting element. Insome embodiments, the IR sensors 336 may include at least one processorconfigured to interpret the returned IR light and determine locationalproperties of targets. The IR sensors 336 may be configured to detectand/or measure a temperature associated with a target (e.g., an object,pedestrian, other vehicle, etc.). Examples of IR sensors 336 asdescribed herein may include, but are not limited to, at least one ofOpto Diode lead-salt IR array sensors, Opto Diode OD-850 Near-IR LEDsensors, Opto Diode SA/SHA727 steady state IR emitters and IR detectors,FLIR® LS microbolometer sensors, FLIR® TacFLIR 380-HD InSb MWIR FPA andHD MWIR thermal sensors, FLIR® VOx 640×480 pixel detector sensors,Delphi IR sensors, other industry-equivalent IR sensors and/or systems,and may perform IR visual target and/or obstacle detection in anenvironment around the vehicle 100 using any known or future-developedstandard and/or architecture.

The vehicle 100 can also include one or more interior sensors 337.Interior sensors 337 can measure characteristics of the insideenvironment of the vehicle 100. The interior sensors 337 may be asdescribed in conjunction with FIG. 3B.

A navigation system 302 can include any hardware and/or software used tonavigate the vehicle either manually or autonomously. The navigationsystem 302 may be as described in conjunction with FIG. 3C.

In some embodiments, the driving vehicle sensors and systems 304 mayinclude other sensors 338 and/or combinations of the sensors 306-337described above. Additionally or alternatively, one or more of thesensors 306-337 described above may include one or more processorsconfigured to process and/or interpret signals detected by the one ormore sensors 306-337. In some embodiments, the processing of at leastsome sensor information provided by the vehicle sensors and systems 304may be processed by at least one sensor processor 340. Raw and/orprocessed sensor data may be stored in a sensor data memory 344 storagemedium. In some embodiments, the sensor data memory 344 may storeinstructions used by the sensor processor 340 for processing sensorinformation provided by the sensors and systems 304. In any event, thesensor data memory 344 may be a disk drive, optical storage device,solid-state storage device such as a random access memory (“RAM”) and/ora read-only memory (“ROM”), which can be programmable, flash-updateable,and/or the like.

The vehicle control system 348 may receive processed sensor informationfrom the sensor processor 340 and determine to control an aspect of thevehicle 100. Controlling an aspect of the vehicle 100 may includepresenting information via one or more display devices 372 associatedwith the vehicle, sending commands to one or more computing devices 368associated with the vehicle, and/or controlling a driving operation ofthe vehicle. In some embodiments, the vehicle control system 348 maycorrespond to one or more computing systems that control drivingoperations of the vehicle 100 in accordance with the Levels of drivingautonomy described above. In one embodiment, the vehicle control system348 may operate a speed of the vehicle 100 by controlling an outputsignal to the accelerator and/or braking system of the vehicle. In thisexample, the vehicle control system 348 may receive sensor datadescribing an environment surrounding the vehicle 100 and, based on thesensor data received, determine to adjust the acceleration, poweroutput, and/or braking of the vehicle 100. The vehicle control system348 may additionally control steering and/or other driving functions ofthe vehicle 100.

The vehicle control system 348 may communicate, in real-time, with thedriving sensors and systems 304 forming a feedback loop. In particular,upon receiving sensor information describing a condition of targets inthe environment surrounding the vehicle 100, the vehicle control system348 may autonomously make changes to a driving operation of the vehicle100. The vehicle control system 348 may then receive subsequent sensorinformation describing any change to the condition of the targetsdetected in the environment as a result of the changes made to thedriving operation. This continual cycle of observation (e.g., via thesensors, etc.) and action (e.g., selected control or non-control ofvehicle operations, etc.) allows the vehicle 100 to operate autonomouslyin the environment.

In some embodiments, the one or more components of the vehicle 100(e.g., the driving vehicle sensors 304, vehicle control system 348,display devices 372, etc.) may communicate across the communicationnetwork 352 to one or more entities 356A-N via a communicationssubsystem 350 of the vehicle 100. Embodiments of the communicationssubsystem 350 are described in greater detail in conjunction with FIG.5. For instance, the navigation sensors 308 may receive globalpositioning, location, and/or navigational information from a navigationsource 356A. In some embodiments, the navigation source 356A may be aglobal navigation satellite system (GNSS) similar, if not identical, toNAVSTAR GPS, GLONASS, EU Galileo, and/or the BeiDou Navigation SatelliteSystem (BDS) to name a few.

In some embodiments, the vehicle control system 348 may receive controlinformation from one or more control sources 356B. The control source356 may provide vehicle control information including autonomous drivingcontrol commands, vehicle operation override control commands, and thelike. The control source 356 may correspond to an autonomous vehiclecontrol system, a traffic control system, an administrative controlentity, and/or some other controlling server. It is an aspect of thepresent disclosure that the vehicle control system 348 and/or othercomponents of the vehicle 100 may exchange communications with thecontrol source 356 across the communication network 352 and via thecommunications subsystem 350.

Information associated with controlling driving operations of thevehicle 100 may be stored in a control data memory 364 storage medium.The control data memory 364 may store instructions used by the vehiclecontrol system 348 for controlling driving operations of the vehicle100, historical control information, autonomous driving control rules,and the like. In some embodiments, the control data memory 364 may be adisk drive, optical storage device, solid-state storage device such as arandom access memory (“RAM”) and/or a read-only memory (“ROM”), whichcan be programmable, flash-updateable, and/or the like.

In addition to the mechanical components described herein, the vehicle100 may include a number of user interface devices. The user interfacedevices receive and translate human input into a mechanical movement orelectrical signal or stimulus. The human input may be one or more ofmotion (e.g., body movement, body part movement, in two-dimensional orthree-dimensional space, etc.), voice, touch, and/or physicalinteraction with the components of the vehicle 100. In some embodiments,the human input may be configured to control one or more functions ofthe vehicle 100 and/or systems of the vehicle 100 described herein. Userinterfaces may include, but are in no way limited to, at least onegraphical user interface of a display device, steering wheel ormechanism, transmission lever or button (e.g., including park, neutral,reverse, and/or drive positions, etc.), throttle control pedal ormechanism, brake control pedal or mechanism, power control switch,communications equipment, etc.

FIG. 3B shows a block diagram of an embodiment of interior sensors 337for a vehicle 100. The interior sensors 337 may be arranged into one ormore groups, based at least partially on the function of the interiorsensors 337. For example, the interior space of a vehicle 100 mayinclude environmental sensors, a user interface sensors, and/or safetysensors. Additionally or alternatively, there may be sensors associatedwith various devices inside the vehicle (e.g., smart phones, tablets,mobile computers, wearables, etc.)

Environmental sensors may comprise sensors configured to collect datarelating to the internal environment of a vehicle 100. Examples ofenvironmental sensors may include one or more of, but are not limitedto: oxygen/air sensors 301, temperature sensors 303, humidity sensors305, light/photo sensors 307, and more. The oxygen/air sensors 301 maybe configured to detect a quality or characteristic of the air in theinterior space 108 of the vehicle 100 (e.g., ratios and/or types ofgasses comprising the air inside the vehicle 100, dangerous gas levels,safe gas levels, etc.). Temperature sensors 303 may be configured todetect temperature readings of one or more objects, users 216, and/orareas of a vehicle 100. Humidity sensors 305 may detect an amount ofwater vapor present in the air inside the vehicle 100. The light/photosensors 307 can detect an amount of light present in the vehicle 100.Further, the light/photo sensors 307 may be configured to detect variouslevels of light intensity associated with light in the vehicle 100.

User interface sensors may comprise sensors configured to collect datarelating to one or more users (e.g., a driver and/or passenger(s)) in avehicle 100. As can be appreciated, the user interface sensors mayinclude sensors that are configured to collect data from users 216 inone or more areas of the vehicle 100. Examples of user interface sensorsmay include one or more of, but are not limited to: infrared sensors309, motion sensors 311, weight sensors 313, wireless network sensors315, biometric sensors 317, camera (or image) sensors 319, audio sensors321, and more.

Infrared sensors 309 may be used to measure IR light irradiating from atleast one surface, user, or another object in the vehicle 100. Amongother things, the Infrared sensors 309 may be used to measuretemperatures, form images (especially in low light conditions), identifyusers 216, and even detect motion in the vehicle 100.

The motion sensors 311 may detect motion and/or movement of objectsinside the vehicle 104. Optionally, the motion sensors 311 may be usedalone or in combination to detect movement. For example, a user may beoperating a vehicle 100 (e.g., while driving, etc.) when a passenger inthe rear of the vehicle 100 unbuckles a safety belt and proceeds to moveabout the vehicle 10. In this example, the movement of the passengercould be detected by the motion sensors 311. In response to detectingthe movement and/or the direction associated with the movement, thepassenger may be prevented from interfacing with and/or accessing atleast some of the vehicle control features. As can be appreciated, theuser may be alerted of the movement/motion such that the user can act toprevent the passenger from interfering with the vehicle controls.Optionally, the number of motion sensors in a vehicle may be increasedto increase an accuracy associated with motion detected in the vehicle100.

Weight sensors 313 may be employed to collect data relating to objectsand/or users in various areas of the vehicle 100. In some cases, theweight sensors 313 may be included in the seats and/or floor of avehicle 100. Optionally, the vehicle 100 may include a wireless networksensor 315. This sensor 315 may be configured to detect one or morewireless network(s) inside the vehicle 100. Examples of wirelessnetworks may include, but are not limited to, wireless communicationsutilizing Bluetooth®, Wi-Fi™, ZigBee, IEEE 802.11, and other wirelesstechnology standards. For example, a mobile hotspot may be detectedinside the vehicle 100 via the wireless network sensor 315. In thiscase, the vehicle 100 may determine to utilize and/or share the mobilehotspot detected via/with one or more other devices associated with thevehicle 100.

Biometric sensors 317 may be employed to identify and/or recordcharacteristics associated with a user. It is anticipated that biometricsensors 317 can include at least one of image sensors, IR sensors,fingerprint readers, weight sensors, load cells, force transducers,heart rate monitors, blood pressure monitors, and the like as providedherein.

The camera sensors 319 may record still images, video, and/orcombinations thereof. Camera sensors 319 may be used alone or incombination to identify objects, users, and/or other features, insidethe vehicle 100. Two or more camera sensors 319 may be used incombination to form, among other things, stereo and/or three-dimensional(3D) images. The stereo images can be recorded and/or used to determinedepth associated with objects and/or users in a vehicle 100. Further,the camera sensors 319 used in combination may determine the complexgeometry associated with identifying characteristics of a user. Forexample, the camera sensors 319 may be used to determine dimensionsbetween various features of a user's face (e.g., the depth/distance froma user's nose to a user's cheeks, a linear distance between the centerof a user's eyes, and more). These dimensions may be used to verify,record, and even modify characteristics that serve to identify a user.The camera sensors 319 may also be used to determine movement associatedwith objects and/or users within the vehicle 100. It should beappreciated that the number of image sensors used in a vehicle 100 maybe increased to provide greater dimensional accuracy and/or views of adetected image in the vehicle 100.

The audio sensors 321 may be configured to receive audio input from auser of the vehicle 100. The audio input from a user may correspond tovoice commands, conversations detected in the vehicle 100, phone callsmade in the vehicle 100, and/or other audible expressions made in thevehicle 100. Audio sensors 321 may include, but are not limited to,microphones and other types of acoustic-to-electric transducers orsensors. Optionally, the interior audio sensors 321 may be configured toreceive and convert sound waves into an equivalent analog or digitalsignal. The interior audio sensors 321 may serve to determine one ormore locations associated with various sounds in the vehicle 100. Thelocation of the sounds may be determined based on a comparison of volumelevels, intensity, and the like, between sounds detected by two or moreinterior audio sensors 321. For instance, a first audio sensor 321 maybe located in a first area of the vehicle 100 and a second audio sensor321 may be located in a second area of the vehicle 100. If a sound isdetected at a first volume level by the first audio sensors 321 A and asecond, higher, volume level by the second audio sensors 321 in thesecond area of the vehicle 100, the sound may be determined to be closerto the second area of the vehicle 100. As can be appreciated, the numberof sound receivers used in a vehicle 100 may be increased (e.g., morethan two, etc.) to increase measurement accuracy surrounding sounddetection and location, or source, of the sound (e.g., viatriangulation, etc.).

The safety sensors may comprise sensors configured to collect datarelating to the safety of a user and/or one or more components of avehicle 100. Examples of safety sensors may include one or more of, butare not limited to: force sensors 325, mechanical motion sensors 327,orientation sensors 329, restraint sensors 331, and more.

The force sensors 325 may include one or more sensors inside the vehicle100 configured to detect a force observed in the vehicle 100. Oneexample of a force sensor 325 may include a force transducer thatconverts measured forces (e.g., force, weight, pressure, etc.) intooutput signals. Mechanical motion sensors 327 may correspond toencoders, accelerometers, damped masses, and the like. Optionally, themechanical motion sensors 327 may be adapted to measure the force ofgravity (i.e., G-force) as observed inside the vehicle 100. Measuringthe G-force observed inside a vehicle 100 can provide valuableinformation related to a vehicle's acceleration, deceleration,collisions, and/or forces that may have been suffered by one or moreusers in the vehicle 100. Orientation sensors 329 can includeaccelerometers, gyroscopes, magnetic sensors, and the like that areconfigured to detect an orientation associated with the vehicle 100.

The restraint sensors 331 may correspond to sensors associated with oneor more restraint devices and/or systems in a vehicle 100. Seatbelts andairbags are examples of restraint devices and/or systems. As can beappreciated, the restraint devices and/or systems may be associated withone or more sensors that are configured to detect a state of thedevice/system. The state may include extension, engagement, retraction,disengagement, deployment, and/or other electrical or mechanicalconditions associated with the device/system.

The associated device sensors 323 can include any sensors that areassociated with a device in the vehicle 100. As previously stated,typical devices may include smart phones, tablets, laptops, mobilecomputers, and the like. It is anticipated that the various sensorsassociated with these devices can be employed by the vehicle controlsystem 348. For example, a typical smart phone can include, an imagesensor, an IR sensor, audio sensor, gyroscope, accelerometer, wirelessnetwork sensor, fingerprint reader, and more. It is an aspect of thepresent disclosure that one or more of these associated device sensors323 may be used by one or more subsystems of the vehicle 100.

FIG. 3C illustrates a GPS/Navigation subsystem(s) 302. The navigationsubsystem(s) 302 can be any present or future-built navigation systemthat may use location data, for example, from the Global PositioningSystem (GPS), to provide navigation information or control the vehicle100. The navigation subsystem(s) 302 can include several components,such as, one or more of, but not limited to: a GPS Antenna/receiver 331,a location module 333, a maps database 335, etc. Generally, the severalcomponents or modules 331-335 may be hardware, software, firmware,computer readable media, or combinations thereof.

A GPS Antenna/receiver 331 can be any antenna, GPS puck, and/or receivercapable of receiving signals from a GPS satellite or other navigationsystem. The signals may be demodulated, converted, interpreted, etc. bythe GPS Antenna/receiver 331 and provided to the location module 333.Thus, the GPS Antenna/receiver 331 may convert the time signals from theGPS system and provide a location (e.g., coordinates on a map) to thelocation module 333. Alternatively, the location module 333 caninterpret the time signals into coordinates or other locationinformation.

The location module 333 can be the controller of the satellitenavigation system designed for use in the vehicle 100. The locationmodule 333 can acquire position data, as from the GPS Antenna/receiver331, to locate the user or vehicle 100 on a road in the unit's mapdatabase 335. Using the road database 335, the location module 333 cangive directions to other locations along roads also in the database 335.When a GPS signal is not available, the location module 333 may applydead reckoning to estimate distance data from sensors 304 including oneor more of, but not limited to, a speed sensor attached to the drivetrain of the vehicle 100, a gyroscope, an accelerometer, etc.Additionally or alternatively, the location module 333 may use knownlocations of Wi-Fi hotspots, cell tower data, etc. to determine theposition of the vehicle 100, such as by using time difference of arrival(TDOA) and/or frequency difference of arrival (FDOA) techniques.

The maps database 335 can include any hardware and/or software to storeinformation about maps, geographical information system (GIS)information, location information, etc. The maps database 335 caninclude any data definition or other structure to store the information.Generally, the maps database 335 can include a road database that mayinclude one or more vector maps of areas of interest. Street names,street numbers, house numbers, and other information can be encoded asgeographic coordinates so that the user can find some desireddestination by street address. Points of interest (waypoints) can alsobe stored with their geographic coordinates. For example, a point ofinterest may include speed cameras, fuel stations, public parking, and“parked here” (or “you parked here”) information. The maps database 335may also include road or street characteristics, for example, speedlimits, location of stop lights/stop signs, lane divisions, schoollocations, etc. The map database contents can be produced or updated bya server connected through a wireless system in communication with theInternet, even as the vehicle 100 is driven along existing streets,yielding an up-to-date map.

FIG. 4 shows one embodiment of the instrument panel 400 of the vehicle100. The instrument panel 400 of vehicle 100 comprises a steering wheel410, a vehicle operational display 420 (e.g., configured to presentand/or display driving data such as speed, measured air resistance,vehicle information, entertainment information, etc.), one or moreauxiliary displays 424 (e.g., configured to present and/or displayinformation segregated from the operational display 420, entertainmentapplications, movies, music, etc.), a heads-up display 434 (e.g.,configured to display any information previously described including,but in no way limited to, guidance information such as route todestination, or obstacle warning information to warn of a potentialcollision, or some or all primary vehicle operational data such asspeed, resistance, etc.), a power management display 428 (e.g.,configured to display data corresponding to electric power levels ofvehicle 100, reserve power, charging status, etc.), and an input device432 (e.g., a controller, touchscreen, or other interface deviceconfigured to interface with one or more displays in the instrumentpanel or components of the vehicle 100. The input device 432 may beconfigured as a joystick, mouse, touchpad, tablet, 3D gesture capturedevice, etc.). In some embodiments, the input device 432 may be used tomanually maneuver a portion of the vehicle 100 into a charging position(e.g., moving a charging plate to a desired separation distance, etc.).

While one or more of displays of instrument panel 400 may betouch-screen displays, it should be appreciated that the vehicleoperational display may be a display incapable of receiving touch input.For instance, the operational display 420 that spans across an interiorspace centerline 404 and across both a first zone 408A and a second zone408B may be isolated from receiving input from touch, especially from apassenger. In some cases, a display that provides vehicle operation orcritical systems information and interface may be restricted fromreceiving touch input and/or be configured as a non-touch display. Thistype of configuration can prevent dangerous mistakes in providing touchinput where such input may cause an accident or unwanted control.

In some embodiments, one or more displays of the instrument panel 400may be mobile devices and/or applications residing on a mobile devicesuch as a smart phone. Additionally or alternatively, any of theinformation described herein may be presented to one or more portions420A-N of the operational display 420 or other display 424, 428, 434. Inone embodiment, one or more displays of the instrument panel 400 may bephysically separated or detached from the instrument panel 400. In somecases, a detachable display may remain tethered to the instrument panel.

The portions 420A-N of the operational display 420 may be dynamicallyreconfigured and/or resized to suit any display of information asdescribed. Additionally or alternatively, the number of portions 420A-Nused to visually present information via the operational display 420 maybe dynamically increased or decreased as required, and are not limitedto the configurations shown.

FIG. 5 illustrates a hardware diagram of communications componentry thatcan be optionally associated with the vehicle 100 in accordance withembodiments of the present disclosure.

The communications componentry can include one or more wired or wirelessdevices such as a transceiver(s) and/or modem that allows communicationsnot only between the various systems disclosed herein but also withother devices, such as devices on a network, and/or on a distributednetwork such as the Internet and/or in the cloud and/or with anothervehicle(s).

The communications subsystem 350 can also include inter- andintra-vehicle communications capabilities such as hotspot and/or accesspoint connectivity for any one or more of the vehicle occupants and/orvehicle-to-vehicle communications.

Additionally, and while not specifically illustrated, the communicationssubsystem 350 can include one or more communications links (that can bewired or wireless) and/or communications busses (managed by the busmanager 574), including one or more of CANbus, OBD-II, ARCINC 429,Byteflight, CAN (Controller Area Network), D2B (Domestic Digital Bus),FlexRay, DC-BUS, IDB-1394, IEBus, I2C, ISO 9141-1/-2, J1708, J1587,J1850, J1939, ISO 11783, Keyword Protocol 2000, LIN (Local InterconnectNetwork), MOST (Media Oriented Systems Transport), Multifunction VehicleBus, SMARTwireX, SPI, VAN (Vehicle Area Network), and the like or ingeneral any communications protocol and/or standard(s).

The various protocols and communications can be communicated one or moreof wirelessly and/or over transmission media such as single wire,twisted pair, fiber optic, IEEE 1394, MIL-STD-1553, MIL-STD-1773,power-line communication, or the like. (All of the above standards andprotocols are incorporated herein by reference in their entirety).

As discussed, the communications subsystem 350 enables communicationsbetween any if the inter-vehicle systems and subsystems as well ascommunications with non-collocated resources, such as those reachableover a network such as the Internet.

The communications subsystem 350, in addition to well-known componentry(which has been omitted for clarity), includes interconnected elementsincluding one or more of: one or more antennas 504, aninterleaver/deinterleaver 508, an analog front end (AFE) 512,memory/storage/cache 516, controller/microprocessor 520, MAC circuitry522, modulator/demodulator 524, encoder/decoder 528, a plurality ofconnectivity managers 534, 558, 562, 566, GPU 540, accelerator 544, amultiplexer/demultiplexer 552, transmitter 570, receiver 572 andwireless radio 578 components such as a Wi-Fi PHY/Bluetooth® module 580,a Wi-Fi/BT MAC module 584, transmitter 588 and receiver 592. The variouselements in the device 350 are connected by one or more links/busses 5(not shown, again for sake of clarity).

The device 350 can have one more antennas 504, for use in wirelesscommunications such as multi-input multi-output (MIMO) communications,multi-user multi-input multi-output (MU-MIMO) communications Bluetooth®,LTE, 4G, 5G, Near-Field Communication (NFC), etc., and in general forany type of wireless communications. The antenna(s) 504 can include, butare not limited to one or more of directional antennas, omnidirectionalantennas, monopoles, patch antennas, loop antennas, microstrip antennas,dipoles, and any other antenna(s) suitable for communicationtransmission/reception. In an exemplary embodiment,transmission/reception using MIMO may require particular antennaspacing. In another exemplary embodiment, MIMO transmission/receptioncan enable spatial diversity allowing for different channelcharacteristics at each of the antennas. In yet another embodiment, MIMOtransmission/reception can be used to distribute resources to multipleusers for example within the vehicle 100 and/or in another vehicle.

Antenna(s) 504 generally interact with the Analog Front End (AFE) 512,which is needed to enable the correct processing of the receivedmodulated signal and signal conditioning for a transmitted signal. TheAFE 512 can be functionally located between the antenna and a digitalbaseband system to convert the analog signal into a digital signal forprocessing and vice-versa.

The subsystem 350 can also include a controller/microprocessor 520 and amemory/storage/cache 516. The subsystem 350 can interact with thememory/storage/cache 516 which may store information and operationsnecessary for configuring and transmitting or receiving the informationdescribed herein. The memory/storage/cache 516 may also be used inconnection with the execution of application programming or instructionsby the controller/microprocessor 520, and for temporary or long termstorage of program instructions and/or data. As examples, thememory/storage/cache 520 may comprise a computer-readable device, RAM,ROM, DRAM, SDRAM, and/or other storage device(s) and media.

The controller/microprocessor 520 may comprise a general purposeprogrammable processor or controller for executing applicationprogramming or instructions related to the subsystem 350. Furthermore,the controller/microprocessor 520 can perform operations for configuringand transmitting/receiving information as described herein. Thecontroller/microprocessor 520 may include multiple processor cores,and/or implement multiple virtual processors. Optionally, thecontroller/microprocessor 520 may include multiple physical processors.By way of example, the controller/microprocessor 520 may comprise aspecially configured Application Specific Integrated Circuit (ASIC) orother integrated circuit, a digital signal processor(s), a controller, ahardwired electronic or logic circuit, a programmable logic device orgate array, a special purpose computer, or the like.

The subsystem 350 can further include a transmitter 570 and receiver 572which can transmit and receive signals, respectively, to and from otherdevices, subsystems and/or other destinations using the one or moreantennas 504 and/or links/busses. Included in the subsystem 350circuitry is the medium access control or MAC Circuitry 522. MACcircuitry 522 provides for controlling access to the wireless medium. Inan exemplary embodiment, the MAC circuitry 522 may be arranged tocontend for the wireless medium and configure frames or packets forcommunicating over the wired/wireless medium.

The subsystem 350 can also optionally contain a security module (notshown). This security module can contain information regarding but notlimited to, security parameters required to connect the device to one ormore other devices or other available network(s), and can include WEP orWPA/WPA-2 (optionally+AES and/or TKIP) security access keys, networkkeys, etc. The WEP security access key is a security password used byWi-Fi networks. Knowledge of this code can enable a wireless device toexchange information with an access point and/or another device. Theinformation exchange can occur through encoded messages with the WEPaccess code often being chosen by the network administrator. WPA is anadded security standard that is also used in conjunction with networkconnectivity with stronger encryption than WEP.

In some embodiments, the communications subsystem 350 also includes aGPU 540, an accelerator 544, a Wi-Fi/BT/BLE PHY module 580 and aWi-Fi/BT/BLE MAC module 584 and wireless transmitter 588 and receiver592. In some embodiments, the GPU 540 may be a graphics processing unit,or visual processing unit, comprising at least one circuit and/or chipthat manipulates and changes memory to accelerate the creation of imagesin a frame buffer for output to at least one display device. The GPU 540may include one or more of a display device connection port, printedcircuit board (PCB), a GPU chip, a metal-oxide-semiconductorfield-effect transistor (MOSFET), memory (e.g., single data raterandom-access memory (SDRAM), double data rate random-access memory(DDR) RAM, etc., and/or combinations thereof), a secondary processingchip (e.g., handling video out capabilities, processing, and/or otherfunctions in addition to the GPU chip, etc.), a capacitor, heatsink,temperature control or cooling fan, motherboard connection, shielding,and the like.

The various connectivity managers 534, 558, 562, 566 manage and/orcoordinate communications between the subsystem 350 and one or more ofthe systems disclosed herein and one or more other devices/systems. Theconnectivity managers 534, 558, 562, 566 include a charging connectivitymanager 534, a vehicle database connectivity manager 558, a remoteoperating system connectivity manager 562, and a sensor connectivitymanager 566.

The charging connectivity manager 534 can coordinate not only thephysical connectivity between the vehicle 100 and a chargingdevice/vehicle, but can also communicate with one or more of a powermanagement controller, one or more third parties and optionally abilling system(s). As an example, the vehicle 100 can establishcommunications with the charging device/vehicle to one or more ofcoordinate interconnectivity between the two (e.g., by spatiallyaligning the charging receptacle on the vehicle with the charger on thecharging vehicle) and optionally share navigation information. Oncecharging is complete, the amount of charge provided can be tracked andoptionally forwarded to, for example, a third party for billing. Inaddition to being able to manage connectivity for the exchange of power,the charging connectivity manager 534 can also communicate information,such as billing information to the charging vehicle and/or a thirdparty. This billing information could be, for example, the owner of thevehicle, the driver/occupant(s) of the vehicle, company information, orin general any information usable to charge the appropriate entity forthe power received.

The vehicle database connectivity manager 558 allows the subsystem toreceive and/or share information stored in the vehicle database. Thisinformation can be shared with other vehicle components/subsystemsand/or other entities, such as third parties and/or charging systems.The information can also be shared with one or more vehicle occupantdevices, such as an app (application) on a mobile device the driver usesto track information about the vehicle 100 and/or a dealer orservice/maintenance provider. In general any information stored in thevehicle database can optionally be shared with any one or more otherdevices optionally subject to any privacy or confidentiallyrestrictions.

The remote operating system connectivity manager 562 facilitatescommunications between the vehicle 100 and any one or more autonomousvehicle systems. These communications can include one or more ofnavigation information, vehicle information, other vehicle information,weather information, occupant information, or in general any informationrelated to the remote operation of the vehicle 100.

The sensor connectivity manager 566 facilitates communications betweenany one or more of the vehicle sensors (e.g., the driving vehiclesensors and systems 304, etc.) and any one or more of the other vehiclesystems. The sensor connectivity manager 566 can also facilitatecommunications between any one or more of the sensors and/or vehiclesystems and any other destination, such as a service company, app, or ingeneral to any destination where sensor data is needed.

In accordance with one exemplary embodiment, any of the communicationsdiscussed herein can be communicated via the conductor(s) used forcharging. One exemplary protocol usable for these communications isPower-line communication (PLC). PLC is a communication protocol thatuses electrical wiring to simultaneously carry both data, andAlternating Current (AC) electric power transmission or electric powerdistribution. It is also known as power-line carrier, power-line digitalsubscriber line (PDSL), mains communication, power-linetelecommunications, or power-line networking (PLN). For DC environmentsin vehicles PLC can be used in conjunction with CAN-bus, LIN-bus overpower line (DC-LIN) and DC-BUS.

The communications subsystem can also optionally manage one or moreidentifiers, such as an IP (internet protocol) address(es), associatedwith the vehicle and one or other system or subsystems or componentstherein. These identifiers can be used in conjunction with any one ormore of the connectivity managers as discussed herein.

FIG. 6 illustrates a block diagram of a computing environment 600 thatmay function as the servers, user computers, or other systems providedand described herein. The computing environment 600 includes one or moreuser computers, or computing devices, such as a vehicle computing device604, a communication device 608, and/or more 612. The computing devices604, 608, 612 may include general purpose personal computers (including,merely by way of example, personal computers, and/or laptop computersrunning various versions of Microsoft Corp.'s Windows® and/or AppleCorp.'s Macintosh® operating systems) and/or workstation computersrunning any of a variety of commercially-available UNIX® or UNIX-likeoperating systems. These computing devices 604, 608, 612 may also haveany of a variety of applications, including for example, database clientand/or server applications, and web browser applications. Alternatively,the computing devices 604, 608, 612 may be any other electronic device,such as a thin-client computer, Internet-enabled mobile telephone,and/or personal digital assistant, capable of communicating via anetwork 352 and/or displaying and navigating web pages or other types ofelectronic documents. Although the exemplary computing environment 600is shown with two computing devices, any number of user computers orcomputing devices may be supported.

The computing environment 600 may also include one or more servers 614,616. In this example, server 614 is shown as a web server and server 616is shown as an application server. The web server 614, which may be usedto process requests for web pages or other electronic documents fromcomputing devices 604, 608, 612. The web server 614 can be running anoperating system including any of those discussed above, as well as anycommercially-available server operating systems. The web server 614 canalso run a variety of server applications, including SIP (SessionInitiation Protocol) servers, HTTP(s) servers, FTP servers, CGI servers,database servers, Java servers, and the like. In some instances, the webserver 614 may publish operations available operations as one or moreweb services.

The computing environment 600 may also include one or more file andor/application servers 616, which can, in addition to an operatingsystem, include one or more applications accessible by a client runningon one or more of the computing devices 604, 608, 612. The server(s) 616and/or 614 may be one or more general purpose computers capable ofexecuting programs or scripts in response to the computing devices 604,608, 612. As one example, the server 616, 614 may execute one or moreweb applications. The web application may be implemented as one or morescripts or programs written in any programming language, such as Java™,C, C#®, or C++, and/or any scripting language, such as Perl, Python, orTCL, as well as combinations of any programming/scripting languages. Theapplication server(s) 616 may also include database servers, includingwithout limitation those commercially available from Oracle®,Microsoft®, Sybase®, IBM® and the like, which can process requests fromdatabase clients running on a computing device 604, 608, 612.

The web pages created by the server 614 and/or 616 may be forwarded to acomputing device 604, 608, 612 via a web (file) server 614, 616.Similarly, the web server 614 may be able to receive web page requests,web services invocations, and/or input data from a computing device 604,608, 612 (e.g., a user computer, etc.) and can forward the web pagerequests and/or input data to the web (application) server 616. Infurther embodiments, the server 616 may function as a file server.Although for ease of description, FIG. 6 illustrates a separate webserver 614 and file/application server 616, those skilled in the artwill recognize that the functions described with respect to servers 614,616 may be performed by a single server and/or a plurality ofspecialized servers, depending on implementation-specific needs andparameters. The computer systems 604, 608, 612, web (file) server 614and/or web (application) server 616 may function as the system, devices,or components described in FIGS. 1-6.

The computing environment 600 may also include a database 618. Thedatabase 618 may reside in a variety of locations. By way of example,database 618 may reside on a storage medium local to (and/or residentin) one or more of the computers 604, 608, 612, 614, 616. Alternatively,it may be remote from any or all of the computers 604, 608, 612, 614,616, and in communication (e.g., via the network 610) with one or moreof these. The database 618 may reside in a storage-area network (“SAN”)familiar to those skilled in the art. Similarly, any necessary files forperforming the functions attributed to the computers 604, 608, 612, 614,616 may be stored locally on the respective computer and/or remotely, asappropriate. The database 618 may be a relational database, such asOracle 20i®, that is adapted to store, update, and retrieve data inresponse to SQL-formatted commands.

FIG. 7 illustrates one embodiment of a computer system 700 upon whichthe servers, user computers, computing devices, or other systems orcomponents described above may be deployed or executed. The computersystem 700 is shown comprising hardware elements that may beelectrically coupled via a bus 704. The hardware elements may includeone or more central processing units (CPUs) 708; one or more inputdevices 712 (e.g., a mouse, a keyboard, etc.); and one or more outputdevices 716 (e.g., a display device, a printer, etc.). The computersystem 700 may also include one or more storage devices 720. By way ofexample, storage device(s) 720 may be disk drives, optical storagedevices, solid-state storage devices such as a random access memory(“RAM”) and/or a read-only memory (“ROM”), which can be programmable,flash-updateable and/or the like.

The computer system 700 may additionally include a computer-readablestorage media reader 724; a communications system 728 (e.g., a modem, anetwork card (wireless or wired), an infra-red communication device,etc.); and working memory 736, which may include RAM and ROM devices asdescribed above. The computer system 700 may also include a processingacceleration unit 732, which can include a DSP, a special-purposeprocessor, and/or the like.

The computer-readable storage media reader 724 can further be connectedto a computer-readable storage medium, together (and, optionally, incombination with storage device(s) 720) comprehensively representingremote, local, fixed, and/or removable storage devices plus storagemedia for temporarily and/or more permanently containingcomputer-readable information. The communications system 728 may permitdata to be exchanged with a network and/or any other computer describedabove with respect to the computer environments described herein.Moreover, as disclosed herein, the term “storage medium” may representone or more devices for storing data, including read only memory (ROM),random access memory (RAM), magnetic RAM, core memory, magnetic diskstorage mediums, optical storage mediums, flash memory devices and/orother machine readable mediums for storing information.

The computer system 700 may also comprise software elements, shown asbeing currently located within a working memory 736, including anoperating system 740 and/or other code 744. It should be appreciatedthat alternate embodiments of a computer system 700 may have numerousvariations from that described above. For example, customized hardwaremight also be used and/or particular elements might be implemented inhardware, software (including portable software, such as applets), orboth. Further, connection to other computing devices such as networkinput/output devices may be employed.

Examples of the processors 340, 708 as described herein may include, butare not limited to, at least one of Qualcomm® Snapdragon® 800 and 801,Qualcomm® Snapdragon® 620 and 615 with 4G LTE Integration and 64-bitcomputing, Apple® A7 processor with 64-bit architecture, Apple® M7motion coprocessors, Samsung® Exynos® series, the Intel® Core™ family ofprocessors, the Intel® Xeon® family of processors, the Intel® Atom™family of processors, the Intel Itanium® family of processors, Intel®Core® i5-4670K and i7-4770K 22 nm Haswell, Intel® Core® i5-3570K 22 nmIvy Bridge, the AMD® FX™ family of processors, AMD® FX-4300, FX-6300,and FX-8350 32 nm Vishera, AMD® Kaveri processors, Texas Instruments®Jacinto C6000™ automotive infotainment processors, Texas Instruments®OMAP™ automotive-grade mobile processors, ARM® Cortex™-M processors,ARM® Cortex-A and ARM926EJ-S™ processors, other industry-equivalentprocessors, and may perform computational functions using any known orfuture-developed standard, instruction set, libraries, and/orarchitecture.

An embodiment of a system 800 for conducting the processes/methodsdescribed herein may be as shown in FIG. 8. The system 800 has variouscomponents which may, as shown in FIG. 8, be executed by a processor708. However, in other configurations, the components can be hardwareelements, which are formed from gates or circuits in a System-on-Chip(SOC), Application Specific Integrated Circuit (ASIC), and/or a FieldProgrammable Gate Array (FPGA). The components in system 800 can includeone or more of, but are not limited to: a route engine 804, an autonomydetermination component 808, and/or a learning component 812.

The route engine 804 can receive information from the navigation system302, the autonomy determination component 808, and/or the learningcomponent 812. The route engine 804 may determine a best route, whichmay have the most or least amount of autonomous driving availability.The route engine 804 can instruct the navigation system 302 about whichof the available different routes to a destination from the currentlocation is preferred. The navigation system 302 can then use that routeto instruct the vehicle control system 348 controlling the autonomousdriving functions of the vehicle 100.

The autonomy determination component 808 is operable to receiveinformation from the learning component 812 and/or the navigation system302 to provide a determination of the amount of autonomy for the one ormore routes provided by the route engine 804 and/or navigation system302. The autonomy determination component 812 can use the information,as described in conjunction with FIGS. 9A through 9C, store thatinformation, retrieve that information, and/or weight that informationfor determining which route to use. The best route information may alsobe provided by the learning component 812, as the learning component 812can receive information from a communication subsystem 350 from anexternal provider or may learn that information through variousiterations of driving different routes. The information described abovemay be as described in conjunction with FIGS. 9A through 9C and may beweighted based on user preferences. User preferences may be received bythe autonomy determination component 808 and/or previously stored by theautonomy determination component 808.

The learning component 812 can receive, as explained previously,information from the communication subsystem 350 from an externalprovider. For example, a mapping system 356A, a central server, or someother provider may provide different information about routes. Some ofthis information may be stored as static information, as explained inconjunction with FIG. 9A. In other situations, the learning componentcan receive real-time traffic or other types of dynamic info, which maybe stored as data structure 928 described in conjunction with FIG. 9B.Regardless, learning component 812 can continually monitor the contextof the driving situation and provide that information to the autonomydetermination component 808 for determining the best route associatedwith the current driving context.

Embodiments of data structures 900, 928, 952 are shown in FIGS. 9A, 9B,and 9C, which provide information about different routes that may betaken by the vehicle 100. Data structure 900, shown in FIG. 9A, caninclude one or more of, but is not limited to: a route identifier 904,static route characteristic 1 908, static route characteristic 2 912,and/or static route characteristic 3 916. There may be more or fewerroute characteristics than that shown in FIG. 9A, as represented byellipses 920. Each route may have a different data structure, and, assuch, there may be more data structures 900 than that shown in FIG. 9A,as represented by ellipses 924. The route characteristics 908-916 can bedifferent information about the route, including such things as thenumber of stoplights or stop signs on the route, whether there areschool zones on the route, the speed limit of the route, and otherstatic information. This information 908-916 is static as theinformation doesn't change (or changes infrequently) based on time ofday or driving conditions. The static information 908-916 may beassociated with a road, a highway, a portion of a road or highway, orsome other portion of the driving environment.

These static route characteristics 908-916 may be associated with aroute identifier (ID) 904. The route identifier 904 can be analphanumeric identifier, a numeric identifier, a globally uniqueidentifier (GUID), a street name, block addresses, or other types ofidentifiers that can identify the route or street. This routeinformation 904 must be unique among all other routes, allowing thenavigation system 302 to understand the route chosen and to provide thisinformation to the route engine 804.

A set of dynamic route information may be provided in data structure928, as shown in FIG. 9B. Similar to the static route information 900,the dynamic route information 928 includes a route ID 904, which may bethe same or similar to the route ID 904 described in conjunction withFIG. 9A. Further, the dynamic route information data structure 928 caninclude one or more of, but is not limited to: dynamic routecharacteristic 1 932, dynamic route characteristic 2 936, and/or dynamicroute characteristic 3 940. There may be more or fewer dynamic routecharacteristics 932-940 than those shown in FIG. 9B, as represented byellipses 944. Each route identified by a route ID 904 can have adifferent data structure 928, and, as such, there may be more datastructures 928 than that shown in FIG. 9B, as represented by ellipses948.

The dynamic route characteristics 932-940 represent characteristics ofthe routes that change over time or change based on traffic or drivingconditions. The dynamic route characteristics 932-940 can be such thingsas the amount of traffic currently on the route, the speed currentlyobserved in the route, whether an emergency vehicle is using the route,or other types of information. Dynamic route information 932-940 canalso include information about weather or other driving conditions. Thisinformation 932-940 changes consistently, periodically, and/orfrequently and may be obtained by the learning component 812 from anoutside provider or may be provided by another vehicle or by the vehicle100 itself based on observation(s) by one or more sensors 304.

A data structure 952 that stores or manages car and driver informationmay be as shown in FIG. 9C. The data structure 952 can include one ormore of, but is not limited to: a user identifier 956, batteryinformation 960, driver preferences 964, driver activity 968, noveltyinformation 972, weighting information 976, etc. There may be more orfewer driver/vehicle information fields than that shown in FIG. 9C, asrepresented by ellipses 980. Each user may have their own set ofinformation or data structure 952, and, as such, there may be more datastructures 952 than those shown in FIG. 9C, as represented by ellipses934.

A user ID 956 can be any type of identifier (similar to the route ID904) and can include an alphanumeric, a numeric, a GUID, a name, ausername, or other types of user identifiers. The user ID 956 can alsoinclude biometric information that can be used to identify the userautomatically with the sensors 304. The other information 960-976, indata structure 952, allows for customizing route selection based on theuser driving the vehicle 100 and/or one or more users that reside withinthe vehicle 100 as a passenger(s).

Battery information 960 can include any type of information for thebattery, which may change the selection of the route based on the needsfor charging or range ability for a route. As such, the batteryinformation 960 can include a charge level, a rate of discharge, theneed for a charging station, a duration before a charge is needed, etc.This information 960 may be used to select a route where recharging thebattery is possible.

The driver preferences 964 can include any type of learned or inputinformation about how the driver desires the vehicle to proceed on anyroute. For example, some drivers may desire to use surface streets morethan highways, may desire to travel streets with trees rather than moreindustrial areas, may desire to avoid certain areas of a town based oncrime or other conditions, or may include other information. Thesedriver preferences can help determine whether a route is desired by auser.

Driver activity 968 may be a dynamic attribute that determines thecurrent activity of a user within the vehicle. Driver activity 968 caninclude such information as whether the user is texting, using acellphone, using a computer or other device, whether the user seems tobe sleepy or intoxicated, or other types of information. Thus, driveractivity 968 may be information gleaned from biometric sensors 304 orother information. This driver activity information 968 may alsoindicate a time period or duration for an activity, for example, aduration for a meeting that is shown in the user's calendar for a userthat the user is currently engaging in on a cellphone. Such durationinformation may provide a time limit or time minimum for a route. Otherinformation may be included for determining an activity of a user.

Novelty information 972 can be information about the user and differentroutes and whether certain routes have been taken and how often, suchthat, the user does not get bored with the same commute. As such,novelty 972 may help to choose a route not previously, or seldom,selected, based on the user's desire to not travel the same route often.Novelty 972 may also be a security measure to ensure that the user doesnot travel the same route consistently and become a target for nefariousactors.

Weightings 976 can be user-determined or predetermined weightings forthe different types of characteristics of a route. For example, a usermay weight more heavily the speed at which a route is taken rather thananother route characteristic. For example, a user may desire to get to alocation quicker rather than enjoy a novel route set by the novelcharacteristic 972. These weightings may be input by a user or may bepredetermined based on driver characteristics or some other information.

An embodiment of method 1000 for dynamically selecting a route based ona driving context may be as shown in FIG. 10. Generally, the method 1000starts with a start operation 1004 and ends with operation 1028. Themethod 1000 can include more or fewer steps or can arrange the order ofthe steps differently than those shown in FIG. 10. The method 1000 canbe executed as a set of computer-executable instructions executed by acomputer system or processor and encoded or stored on a computerreadable medium. In other configurations, the method 1000 may beexecuted by a series of components, circuits, gates, etc. created in ahardware device, such as a System-on-Chip (SOC), Application SpecificIntegrated Circuit (ASIC), and/or a Field Programmable Gate Array(FPGA). Hereinafter, the method 1000 shall be explained with referenceto the systems, components, circuits, modules, software, datastructures, signalling processes, models, environments, vehicles, etc.described in conjunction with FIGS. 1-9.

The learning component 812 can receive static route characteristics 900,in step 1008. The learning component 812 may receive information 900about different routes from a navigation map supplier 356A through thecommunication system 350. This static route information 900 may also begleaned from other cars or based on graphical information systemdetails. This information may be stored as static route information 900,as described in conjunction with FIG. 9A. Static information 900 may beretrieved by the autonomy determination component 808 from memory 516.

Similarly, the learning component 812 can receive dynamiccharacteristics 928 for routes, in step 1012. The learning component 812may receive information 928 from sensors 304, from other vehicles, orfrom a third-party supplier 356A of real-time traffic or other dynamicinformation through the communication system 350. This dynamicinformation may be stored in dynamic information data structure 928, asdescribed in conjunction with FIG. 9B. The learning component 812 candefine this dynamic information 928, retrieve the information 928 frommemory 516, and provide that information 928 to the autonomydetermination component 808.

User/vehicle information 952 may be retrieved or determined, in step1016. User characteristics and or vehicle characteristics, in datastructure 952 may be obtained from sensor information or frominformation from the vehicle control system 348 or other vehiclesystems. Thus, the battery characteristics 960 and other informationabout the vehicle 100 may also be provided in data structure 952. Thisinformation 952 may be provided to the autonomy determination component808 by retrieving the data structure 952 from memory 516.

In step 1020, the autonomy determination component 808 determines thebest fit for a route based on the different characteristics provided bythe learning component 812 and/or other sources. Using weightings 976,the autonomy determination component 808 can weigh the different factorsof two or more routes. Based on a score that measures the best to theweighted characteristics, the route autonomy determination component 808can give a measure of the level of autonomy possible or a measure thedesired fit of each route to the current driving context. This best fitinformation may then be provided to the route engine 804.

The route engine 804, which provided the different routes to theautonomy determination component 808, can then receive the informationabout the autonomy level or best fit for each route from the autonomydetermination component 808. The route engine 804 may then select thebest route out of the different options and provide that information tothe navigation system 302. The selected route can be the route with thehighest score that correlates to the route that is best for the currentdriving context. The navigation system 302 may then change or select theroute presented to the user and then control the vehicle 348 based onthe amount of autonomy allowed for or other characteristics associatedwith the route.

Any of the steps, functions, and operations discussed herein can beperformed continuously and automatically.

The exemplary systems and methods of this disclosure have been describedin relation to vehicle systems and electric vehicles. However, to avoidunnecessarily obscuring the present disclosure, the precedingdescription omits a number of known structures and devices. Thisomission is not to be construed as a limitation of the scope of theclaimed disclosure. Specific details are set forth to provide anunderstanding of the present disclosure. It should, however, beappreciated that the present disclosure may be practiced in a variety ofways beyond the specific detail set forth herein.

Furthermore, while the exemplary embodiments illustrated herein show thevarious components of the system collocated, certain components of thesystem can be located remotely, at distant portions of a distributednetwork, such as a LAN and/or the Internet, or within a dedicatedsystem. Thus, it should be appreciated, that the components of thesystem can be combined into one or more devices, such as a server,communication device, or collocated on a particular node of adistributed network, such as an analog and/or digital telecommunicationsnetwork, a packet-switched network, or a circuit-switched network. Itwill be appreciated from the preceding description, and for reasons ofcomputational efficiency, that the components of the system can bearranged at any location within a distributed network of componentswithout affecting the operation of the system.

Furthermore, it should be appreciated that the various links connectingthe elements can be wired or wireless links, or any combination thereof,or any other known or later developed element(s) that is capable ofsupplying and/or communicating data to and from the connected elements.These wired or wireless links can also be secure links and may becapable of communicating encrypted information. Transmission media usedas links, for example, can be any suitable carrier for electricalsignals, including coaxial cables, copper wire, and fiber optics, andmay take the form of acoustic or light waves, such as those generatedduring radio-wave and infra-red data communications.

While the flowcharts have been discussed and illustrated in relation toa particular sequence of events, it should be appreciated that changes,additions, and omissions to this sequence can occur without materiallyaffecting the operation of the disclosed embodiments, configuration, andaspects.

A number of variations and modifications of the disclosure can be used.It would be possible to provide for some features of the disclosurewithout providing others.

In yet another embodiment, the systems and methods of this disclosurecan be implemented in conjunction with a special purpose computer, aprogrammed microprocessor or microcontroller and peripheral integratedcircuit element(s), an ASIC or other integrated circuit, a digitalsignal processor, a hard-wired electronic or logic circuit such asdiscrete element circuit, a programmable logic device or gate array suchas PLD, PLA, FPGA, PAL, special purpose computer, any comparable means,or the like. In general, any device(s) or means capable of implementingthe methodology illustrated herein can be used to implement the variousaspects of this disclosure. Exemplary hardware that can be used for thepresent disclosure includes computers, handheld devices, telephones(e.g., cellular, Internet enabled, digital, analog, hybrids, andothers), and other hardware known in the art. Some of these devicesinclude processors (e.g., a single or multiple microprocessors), memory,nonvolatile storage, input devices, and output devices. Furthermore,alternative software implementations including, but not limited to,distributed processing or component/object distributed processing,parallel processing, or virtual machine processing can also beconstructed to implement the methods described herein.

In yet another embodiment, the disclosed methods may be readilyimplemented in conjunction with software using object or object-orientedsoftware development environments that provide portable source code thatcan be used on a variety of computer or workstation platforms.Alternatively, the disclosed system may be implemented partially orfully in hardware using standard logic circuits or VLSI design. Whethersoftware or hardware is used to implement the systems in accordance withthis disclosure is dependent on the speed and/or efficiency requirementsof the system, the particular function, and the particular software orhardware systems or microprocessor or microcomputer systems beingutilized.

In yet another embodiment, the disclosed methods may be partiallyimplemented in software that can be stored on a storage medium, executedon programmed general-purpose computer with the cooperation of acontroller and memory, a special purpose computer, a microprocessor, orthe like. In these instances, the systems and methods of this disclosurecan be implemented as a program embedded on a personal computer such asan applet, JAVA® or CGI script, as a resource residing on a server orcomputer workstation, as a routine embedded in a dedicated measurementsystem, system component, or the like. The system can also beimplemented by physically incorporating the system and/or method into asoftware and/or hardware system.

Although the present disclosure describes components and functionsimplemented in the embodiments with reference to particular standardsand protocols, the disclosure is not limited to such standards andprotocols. Other similar standards and protocols not mentioned hereinare in existence and are considered to be included in the presentdisclosure. Moreover, the standards and protocols mentioned herein andother similar standards and protocols not mentioned herein areperiodically superseded by faster or more effective equivalents havingessentially the same functions. Such replacement standards and protocolshaving the same functions are considered equivalents included in thepresent disclosure.

The present disclosure, in various embodiments, configurations, andaspects, includes components, methods, processes, systems and/orapparatus substantially as depicted and described herein, includingvarious embodiments, subcombinations, and subsets thereof. Those ofskill in the art will understand how to make and use the systems andmethods disclosed herein after understanding the present disclosure. Thepresent disclosure, in various embodiments, configurations, and aspects,includes providing devices and processes in the absence of items notdepicted and/or described herein or in various embodiments,configurations, or aspects hereof, including in the absence of suchitems as may have been used in previous devices or processes, e.g., forimproving performance, achieving ease, and/or reducing cost ofimplementation.

The foregoing discussion of the disclosure has been presented forpurposes of illustration and description. The foregoing is not intendedto limit the disclosure to the form or forms disclosed herein. In theforegoing Detailed Description for example, various features of thedisclosure are grouped together in one or more embodiments,configurations, or aspects for the purpose of streamlining thedisclosure. The features of the embodiments, configurations, or aspectsof the disclosure may be combined in alternate embodiments,configurations, or aspects other than those discussed above. This methodof disclosure is not to be interpreted as reflecting an intention thatthe claimed disclosure requires more features than are expressly recitedin each claim. Rather, as the following claims reflect, inventiveaspects lie in less than all features of a single foregoing disclosedembodiment, configuration, or aspect. Thus, the following claims arehereby incorporated into this Detailed Description, with each claimstanding on its own as a separate preferred embodiment of thedisclosure.

Moreover, though the description of the disclosure has includeddescription of one or more embodiments, configurations, or aspects andcertain variations and modifications, other variations, combinations,and modifications are within the scope of the disclosure, e.g., as maybe within the skill and knowledge of those in the art, afterunderstanding the present disclosure. It is intended to obtain rights,which include alternative embodiments, configurations, or aspects to theextent permitted, including alternate, interchangeable and/or equivalentstructures, functions, ranges, or steps to those claimed, whether or notsuch alternate, interchangeable and/or equivalent structures, functions,ranges, or steps are disclosed herein, and without intending to publiclydedicate any patentable subject matter.

Embodiments include a vehicle, comprising: a sensor to sense anenvironment surrounding the vehicle; a vehicle control system toautonomously control driving functions of the vehicle; a navigationsystem, in communication with the sensor and the vehicle control system,to provide a selected route to the vehicle control system forautonomously controlling the vehicle along the selected route; and aprocessor, in communication with the sensor, the navigation system, andthe vehicle control system, to: receive characteristics associated withtwo or more routes between a start point and an end point, wherein thecharacteristics define a driving context for each of the two or moreroutes; based on the characteristics, determine the selected route ofthe two or more routes that best fits the driving context and providethe selected route to the navigation system.

Any of the one or more above aspects, wherein the characteristicsinclude one or more of a static characteristic, a dynamiccharacteristic, a user characteristic, and/or a vehicle characteristic.

Any of the one or more above aspects, wherein the static characteristicincludes one or more of an average number of lanes in each route segmentalong every viable route, an average number of traffic lights, a numberof school zones, a number of stop signs, a number of yield signs, anumber of lane merges, an average speed limit, and/or historical trafficor road occupant density for motorcycles, cars, trucks, cyclists, and/orpedestrians.

Any of the one or more above aspects, wherein the dynamic characteristicincludes one or more of an amount of traffic currently on the route, aspeed currently observed in the route, whether an emergency vehicle isusing the route, weather and/or a driving condition.

Any of the one or more above aspects, wherein the user characteristicincludes one or more of a driver preference, a driver activity, noveltyinformation, and/or weighting information.

Any of the one or more above aspects, wherein the vehicle characteristicincludes battery information.

Any of the one or more above aspects, wherein the battery informationincludes one or more of a charge level, a rate of discharge, a need fora charging station, and/or a duration before a charge is needed.

Any of the one or more above aspects, wherein a longer route is chosenbased on an event in a user's calendar being conducted in the vehicle.

Any of the one or more above aspects, wherein the processor determinesthe best fit for the two or more routes by weighting thecharacteristics.

Any of the one or more above aspects, wherein the processor determines abest score based on the weighted characteristics.

Any of the one or more above aspects, wherein the route with the bestscore is the selected route.

Embodiments include a method, comprising: a processor receivingcharacteristics associated with two or more routes, for a vehicle,between a start point and an end point, wherein the characteristicsdefine a driving context for each of the two or more routes; based onthe characteristics, the processor determining a selected route of thetwo or more routes that best fits the driving context the processorproviding the selected route to a navigation system; the navigationsystem providing route directions for the selected route to a vehiclecontrol system for autonomously controlling the vehicle along theselected route; and the vehicle control system autonomously controllingdriving functions of the vehicle to maneuver the vehicle along theselected route.

Any of the one or more above aspects, wherein the characteristicsinclude one or more of a static characteristic, a dynamiccharacteristic, a user characteristic, and/or a vehicle characteristic.

Any of the one or more above aspects, wherein the static characteristicincludes one or more of an average number of lanes in each route segmentalong every viable route, an average number of traffic lights, a numberof school zones, a number of stop signs, a number of yield signs, anumber of lane merges, an average speed limit, and/or historical trafficor road occupant density for motorcycles, cars, trucks, cyclists, and/orpedestrians.

Any of the one or more above aspects, wherein the dynamic characteristicincludes one or more of an amount of traffic currently on the route, aspeed currently observed in the route, whether an emergency vehicle isusing the route, weather and/or a driving condition.

Any of the one or more above aspects, wherein the processor determinesthe best fit for the two or more routes by weighting thecharacteristics, wherein the processor determines a best score based onthe weighted characteristics, and wherein the route with the best scoreis the selected route.

Embodiments include a non-transitory information storage media havingstored thereon one or more instructions, that when executed by one ormore processors, cause a vehicle to perform a method, the methodcomprising: receiving characteristics associated with two or moreroutes, for a vehicle, between a start point and an end point, whereinthe characteristics define a driving context for each of the two or moreroutes; based on the characteristics, determining a selected route ofthe two or more routes that best fits the driving context providing theselected route to a navigation system; providing route directions forthe selected route to a vehicle control system for autonomouslycontrolling the vehicle along the selected route; and autonomouslycontrolling driving functions of the vehicle to maneuver the vehiclealong the selected route.

Any of the one or more above aspects, wherein the characteristicsinclude one or more of a static characteristic, a dynamiccharacteristic, a user characteristic, and/or a vehicle characteristic,wherein the static characteristic includes one or more of an averagenumber of lanes in each route segment along every viable route, anaverage number of traffic lights, a number of school zones, a number ofstop signs, a number of yield signs, a number of lane merges, an averagespeed limit, and/or historical traffic or road occupant density formotorcycles, cars, trucks, cyclists, and/or pedestrians, and wherein thedynamic characteristic includes one or more of an amount of trafficcurrently on the route, a speed currently observed in the route, whetheran emergency vehicle is using the route, weather and/or a drivingcondition.

Any of the one or more above aspects, wherein the processor determinesthe best fit for the two or more routes by weighting thecharacteristics, wherein the processor determines a best score based onthe weighted characteristics, and wherein the route with the best scoreis the selected route.

Any of the one or more above aspects, wherein a longer route is chosenbased on an event in a user's calendar being conducted in the vehicle,wherein the event is part of a driver activity characteristic.

Any one or more of the aspects/embodiments as substantially disclosedherein.

Any one or more of the aspects/embodiments as substantially disclosedherein optionally in combination with any one or more otheraspects/embodiments as substantially disclosed herein.

One or means adapted to perform any one or more of the aboveaspects/embodiments as substantially disclosed herein.

The phrases “at least one,” “one or more,” “or,” and “and/or” areopen-ended expressions that are both conjunctive and disjunctive inoperation. For example, each of the expressions “at least one of A, Band C,” “at least one of A, B, or C,” “one or more of A, B, and C,” “oneor more of A, B, or C,” “A, B, and/or C,” and “A, B, or C” means Aalone, B alone, C alone, A and B together, A and C together, B and Ctogether, or A, B and C together.

The term “a” or “an” entity refers to one or more of that entity. Assuch, the terms “a” (or “an”), “one or more,” and “at least one” can beused interchangeably herein. It is also to be noted that the terms“comprising,” “including,” and “having” can be used interchangeably.

The term “automatic” and variations thereof, as used herein, refers toany process or operation, which is typically continuous orsemi-continuous, done without material human input when the process oroperation is performed. However, a process or operation can beautomatic, even though performance of the process or operation usesmaterial or immaterial human input, if the input is received beforeperformance of the process or operation. Human input is deemed to bematerial if such input influences how the process or operation will beperformed. Human input that consents to the performance of the processor operation is not deemed to be “material.”

Aspects of the present disclosure may take the form of an embodimentthat is entirely hardware, an embodiment that is entirely software(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module,” or “system.”Any combination of one or more computer-readable medium(s) may beutilized. The computer-readable medium may be a computer-readable signalmedium or a computer-readable storage medium.

A computer-readable storage medium may be, for example, but not limitedto, an electronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device, or any suitable combinationof the foregoing. More specific examples (a non-exhaustive list) of thecomputer-readable storage medium would include the following: anelectrical connection having one or more wires, a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM or Flashmemory), an optical fiber, a portable compact disc read-only memory(CD-ROM), an optical storage device, a magnetic storage device, or anysuitable combination of the foregoing. In the context of this document,a computer-readable storage medium may be any tangible medium that cancontain or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

A computer-readable signal medium may include a propagated data signalwith computer-readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer-readable signal medium may be any computer-readable medium thatis not a computer-readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device. Program codeembodied on a computer-readable medium may be transmitted using anyappropriate medium, including, but not limited to, wireless, wireline,optical fiber cable, RF, etc., or any suitable combination of theforegoing.

The terms “determine,” “calculate,” “compute,” and variations thereof,as used herein, are used interchangeably and include any type ofmethodology, process, mathematical operation or technique.

The term “electric vehicle” (EV), also referred to herein as an electricdrive vehicle, may use one or more electric motors or traction motorsfor propulsion. An electric vehicle may be powered through a collectorsystem by electricity from off-vehicle sources, or may be self-containedwith a battery or generator to convert fuel to electricity. An electricvehicle generally includes a rechargeable electricity storage system(RESS) (also called Full Electric Vehicles (FEV)). Power storage methodsmay include: chemical energy stored on the vehicle in on-board batteries(e.g., battery electric vehicle or BEV), on board kinetic energy storage(e.g., flywheels), and/or static energy (e.g., by on-board double-layercapacitors). Batteries, electric double-layer capacitors, and flywheelenergy storage may be forms of rechargeable on-board electrical storage.

The term “hybrid electric vehicle” refers to a vehicle that may combinea conventional (usually fossil fuel-powered) powertrain with some formof electric propulsion. Most hybrid electric vehicles combine aconventional internal combustion engine (ICE) propulsion system with anelectric propulsion system (hybrid vehicle drivetrain). In parallelhybrids, the ICE and the electric motor are both connected to themechanical transmission and can simultaneously transmit power to drivethe wheels, usually through a conventional transmission. In serieshybrids, only the electric motor drives the drivetrain, and a smallerICE works as a generator to power the electric motor or to recharge thebatteries. Power-split hybrids combine series and parallelcharacteristics. A full hybrid, sometimes also called a strong hybrid,is a vehicle that can run on just the engine, just the batteries, or acombination of both. A mid hybrid is a vehicle that cannot be drivensolely on its electric motor, because the electric motor does not haveenough power to propel the vehicle on its own.

The term “rechargeable electric vehicle” or “REV” refers to a vehiclewith on board rechargeable energy storage, including electric vehiclesand hybrid electric vehicles.

What is claimed is:
 1. A vehicle, comprising: a first set of sensors tosense an environment surrounding the vehicle; a second set of sensors tosense an activity of an occupant in the vehicle; a third set of sensorsto sense a state of the vehicle; a vehicle control system forautonomously controlling driving functions of the vehicle; a navigationsystem, in communication with the first, second, and third sets ofsensors and the vehicle control system, to provide a selected route tothe vehicle control system for autonomously controlling the vehiclealong the selected route; and a processor in communication with thefirst, second, and third sets of sensors, the navigation system, and thevehicle control system, the processor: receiving, from a databaseexternal to the vehicle and for each of two or more routes between acommon start point and a common end point, static route characteristicsthat do not change for each of the two or more routes; receiving, inreal-time from one or more other vehicles, dynamic route characteristicsthat change for each of the two or more routes, wherein each of the twoor more routes has a different set of the static route characteristicsand the dynamic route characteristics; receiving user routecharacteristics that indicate route preferences of the occupant of thevehicle; receiving vehicle characteristics that indicate a state of oneor more components of the vehicle; selecting a level of autonomy, fromamong a plurality of levels of autonomy, based on the sensed activity ofthe occupant; selecting, based on the static route characteristics, thedynamic route characteristics, the user route characteristics, and thevehicle characteristics for each of the two or more routes, a route ofthe two or more routes that best fits the selected level of autonomy,the sensed environment surrounding the vehicle, and the sensed state ofthe vehicle; and providing the selected route to the navigation system.2. The vehicle of claim 1, wherein, for each of the two or more routes,the static route characteristics are received in a first data structurethat includes the static route characteristics and a route ID thatidentifies a respective route, wherein, for each of the two or moreroutes, the dynamic route characteristics are received in a second datastructure that includes the dynamic route characteristics and the routeID that identifies the respective route, and wherein, for each of thetwo or more routes, the user route characteristics are received in athird data structure that includes the user route characteristics and auser ID that identifies the occupant.
 3. The vehicle of claim 1, whereinthe static route characteristics comprise one or more of an averagenumber of lanes in each route segment along every viable route, anaverage number of traffic lights, a number of school zones, a number ofstop signs, a number of yield signs, a number of lane merges, an averagespeed limit, or historical traffic or road occupant density formotorcycles, cars, trucks, cyclists, and pedestrians.
 4. The vehicle ofclaim 1, wherein the dynamic route characteristics comprise one or moreof an amount of traffic currently on each of the two or more routes, aspeed currently observed in each of the two or more routes, whether anemergency vehicle is using each of the two or more routes, weather or adriving condition.
 5. The vehicle of claim 1, wherein the user routecharacteristics comprise novelty information that indicates the occupantof the vehicle desires to vary the selected route as a security measureto ensure the vehicle does not travel a same route consistently.
 6. Thevehicle of claim 5, wherein the user route characteristics compriseweighting information and one or more of a driver preference, and adriver activity, wherein the weighting information includes userpreferences on route speed, route average speed limit, route trafficdensity, or route driving conditions.
 7. The vehicle of claim 6, whereinthe vehicle characteristics include battery information, and wherein thebattery information includes one or more of a charge level, a rate ofdischarge, a need for a charging station, or a duration before a chargeis needed.
 8. The vehicle of claim 1, wherein the processor accesses acalendar of a driver or of a passenger of the vehicle, wherein theprocessor chooses the selected level of autonomy and the selected routebased on an event in the calendar of the driver or of the passenger,wherein the processor chooses a longer route as the selected route tomatch a length of the event in the calendar.
 9. The vehicle of claim 7,wherein the processor determines the selected route as a best fit forthe two or more routes by weighting one or more of the static routecharacteristics, the dynamic route characteristics, the user routecharacteristics, or the vehicle characteristics, wherein the selectedlevel of autonomy is selected from one of level 0, level 1, level 2,level 3, level 4, or level 5, wherein the level 0 corresponds to a “NoAutomation” level where the vehicle is not responsible for any of thedriving functions of the vehicle, wherein the level 1 corresponds to a“Driver Assistance” level where the vehicle controls throttle and/orbraking operations of the driving functions of the vehicle, wherein thelevel 2 corresponds to a “Partial Automation” level where the vehiclecollects information and uses the collected information to control thedriving functions of the vehicle, wherein the level 3 corresponds to a“Conditional Automation” where a driver is separated from controllingall the driving functions of the vehicle except when the vehiclerequests the driver to act or intervene in controlling the drivingfunctions, wherein the level 4 corresponds to a “High Automation” levelwhere the driver is separated from controlling all the driving functionsof the vehicle and the vehicle controls the driving functions of thevehicle even when the driver fails to respond to a request to intervene,wherein the level 5 corresponds to a “Full Automation” level where thevehicle continually monitors all roadway and environmental conditionsand no human driver interaction is required.
 10. The vehicle of claim 9,wherein the processor determines a best score based on the weightedinformation.
 11. The vehicle of claim 10, wherein a route with a bestscore is the selected route.
 12. A method, comprising: receiving, by aprocessor of a vehicle from a database external to the vehicle and foreach of two or more routes between a common start point and a common endpoint, static route characteristics that do not change for each of thetwo or more routes; receiving, by the processor in real-time from one ormore other vehicles, dynamic route characteristics that change for eachof the two or more routes, wherein each of the two or more routes has adifferent set of the static route characteristics and the dynamic routecharacteristics; receiving, by the processor, user route characteristicsthat indicate route preferences of an occupant of the vehicle;receiving, by the processor, vehicle characteristics that indicate astate of one or more components of the vehicle; receiving, by theprocessor, a sensed environment surrounding the vehicle, a sensedactivity of the occupant of the vehicle, and a sensed state of thevehicle; selecting, by the processor, a level of autonomy, from among aplurality of levels of autonomy, based on the sensed activity of theoccupant; selecting, by the processor, based on the static routecharacteristics, the dynamic route characteristics, the user routecharacteristics, and the vehicle characteristics for each of the two ormore routes, a route of the two or more routes that best fits theselected level of autonomy, the sensed environment, and the sensed stateof the vehicle; providing, by the processor, the selected route to anavigation system; providing, by the navigation system, route directionsfor the selected route to a vehicle control system for autonomouslycontrolling the vehicle along the selected route; and controllingautonomously, by the vehicle control system, driving functions of thevehicle to maneuver the vehicle along the selected route.
 13. The methodof claim 12, wherein, for each of the two or more routes, the staticroute characteristics are received in a first data structure thatincludes the static route characteristics and a route ID that identifiesa respective route, wherein, for each of the two or more routes, thedynamic route characteristics are received in a second data structurethat includes the dynamic route characteristics and the route ID thatidentifies the respective route, and wherein, for each of the two ormore routes, the user route characteristics are received in a third datastructure that includes the user route characteristics and a user IDthat identifies the occupant.
 14. The method of claim 13, wherein thestatic route characteristics include one or more of an average number oflanes in each route segment along every viable route, an average numberof traffic lights, a number of school zones, a number of stop signs, anumber of yield signs, a number of lane merges, an average speed limit,or historical traffic or road occupant density for motorcycles, cars,trucks, cyclists, and pedestrians.
 15. The method of claim 13, whereinthe dynamic route characteristics include one or more of an amount oftraffic currently on each of the two or more routes, a speed currentlyobserved in each of the two or more routes, whether an emergency vehicleis using each of the two or more routes, weather, or a drivingcondition.
 16. The method of claim 13, wherein the processor determinesthe selected route as a best fit for the two or more routes by weightingone or more of the static route characteristics, the dynamic routecharacteristics, the user route characteristics, or the vehiclecharacteristics, wherein the processor determines a best score based onthe weighted one or more of the static route characteristics, andwherein a route with a best score is the selected route.
 17. Anon-transitory information storage media having stored thereon one ormore instructions, that when executed by one or more processors, cause avehicle to perform a method, the method, comprising: receiving, from adatabase external to the vehicle for each of two or more routes betweena common start point and a common end point, static routecharacteristics that do not change for each of the two or more routes;receiving, in real-time from one or more other vehicles, dynamic routecharacteristics that change for each of the two or more routes, whereineach of the two or more routes has a different set of the static routecharacteristics and the dynamic route characteristics; receiving userroute characteristics that indicate route preferences of an occupant ofthe vehicle; receiving vehicle characteristics that indicate a state ofone or more components of the vehicle; receiving a sensed environmentsurrounding the vehicle, a sensed activity of the occupant of thevehicle, and a sensed state of the vehicle; selecting a level ofautonomy, from among a plurality of levels of autonomy, based on thesensed activity of the occupant; selecting, based on the sets of staticroute and dynamic route characteristics for each of the two or moreroutes, a route of the two or more routes that best fits the selectedlevel of autonomy, the sensed environment, and the sensed state of thevehicle; providing the selected route to a navigation system; providingroute directions for the selected route to a vehicle control system forautonomously controlling the vehicle along the selected route; andautonomously controlling driving functions of the vehicle to maneuverthe vehicle along the selected route.
 18. The non-transitory informationstorage media of claim 17, wherein, for each of the two or more routes,the static route characteristics are received in a first data structurethat includes the static route characteristics and a route ID thatidentifies a respective route, wherein, for each of the two or moreroutes, the dynamic route characteristics are received in a second datastructure that includes the dynamic route characteristics and the routeID that identifies the respective route, and wherein, for each of thetwo or more routes, the user route characteristics are received in athird data structure that includes the user route characteristics and auser ID that identifies the occupant.
 19. The non-transitory informationstorage media of claim 17, wherein the selected level of autonomy isselected from one of level 0, level 1, level 2, level 3, level 4, orlevel 5, wherein the level 0 corresponds to a “No Automation” levelwhere the vehicle is not responsible for any of the driving functions ofthe vehicle, wherein the level 1 corresponds to a “Driver Assistance”level where the vehicle controls throttle and/or braking operations ofthe driving functions of the vehicle, wherein the level 2 corresponds toa “Partial Automation” level where the vehicle collects information anduses the collected information to control the driving functions of thevehicle, wherein the level 3 corresponds to a “Conditional Automation”where a driver is separated from controlling all the driving functionsof the vehicle except when the vehicle requests the driver to act orintervene in controlling the driving functions of the vehicle, whereinthe level 4 corresponds to a “High Automation” level where the driver isseparated from controlling all the driving functions of the vehicle andthe vehicle controls the driving functions of the vehicle even when thedriver fails to respond to a request to intervene, wherein the level 5corresponds to a “Full Automation” level where the vehicle continuallymonitors all roadway and environmental conditions and no human driverinteraction is required.
 20. The non-transitory information storagemedia of claim 17, wherein a longer route is chosen based on an event inthe occupant's calendar being conducted in the vehicle.